Overview

Dataset statistics

Number of variables10
Number of observations261239
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.9 MiB
Average record size in memory80.0 B

Variable types

Numeric10

Alerts

u is highly correlated with g and 6 other fieldsHigh correlation
g is highly correlated with u and 8 other fieldsHigh correlation
r is highly correlated with u and 8 other fieldsHigh correlation
i is highly correlated with u and 7 other fieldsHigh correlation
z is highly correlated with u and 7 other fieldsHigh correlation
uErr is highly correlated with u and 4 other fieldsHigh correlation
gErr is highly correlated with u and 8 other fieldsHigh correlation
rErr is highly correlated with u and 8 other fieldsHigh correlation
iErr is highly correlated with g and 6 other fieldsHigh correlation
zErr is highly correlated with g and 6 other fieldsHigh correlation
u is highly correlated with g and 6 other fieldsHigh correlation
g is highly correlated with u and 8 other fieldsHigh correlation
r is highly correlated with u and 8 other fieldsHigh correlation
i is highly correlated with u and 8 other fieldsHigh correlation
z is highly correlated with u and 8 other fieldsHigh correlation
uErr is highly correlated with u and 6 other fieldsHigh correlation
gErr is highly correlated with u and 8 other fieldsHigh correlation
rErr is highly correlated with u and 8 other fieldsHigh correlation
iErr is highly correlated with g and 6 other fieldsHigh correlation
zErr is highly correlated with g and 6 other fieldsHigh correlation
u is highly correlated with g and 2 other fieldsHigh correlation
g is highly correlated with u and 6 other fieldsHigh correlation
r is highly correlated with g and 6 other fieldsHigh correlation
i is highly correlated with g and 6 other fieldsHigh correlation
z is highly correlated with g and 6 other fieldsHigh correlation
uErr is highly correlated with u and 1 other fieldsHigh correlation
gErr is highly correlated with u and 7 other fieldsHigh correlation
rErr is highly correlated with g and 6 other fieldsHigh correlation
iErr is highly correlated with g and 6 other fieldsHigh correlation
zErr is highly correlated with r and 4 other fieldsHigh correlation
u is highly correlated with g and 7 other fieldsHigh correlation
g is highly correlated with u and 8 other fieldsHigh correlation
r is highly correlated with u and 8 other fieldsHigh correlation
i is highly correlated with u and 8 other fieldsHigh correlation
z is highly correlated with u and 8 other fieldsHigh correlation
uErr is highly correlated with u and 7 other fieldsHigh correlation
gErr is highly correlated with u and 8 other fieldsHigh correlation
rErr is highly correlated with u and 8 other fieldsHigh correlation
iErr is highly correlated with u and 8 other fieldsHigh correlation
zErr is highly correlated with g and 6 other fieldsHigh correlation

Reproduction

Analysis started2022-02-27 19:49:16.662682
Analysis finished2022-02-27 19:49:39.292232
Duration22.63 seconds
Software versionpandas-profiling v3.1.1
Download configurationconfig.json

Variables

u
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct252294
Distinct (%)96.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.485983709
Minimum4.020049294
Maximum4.843548207
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 MiB
2022-02-27T16:49:39.341899image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum4.020049294
5-th percentile4.235845197
Q14.409907973
median4.504034806
Q34.580414819
95-th percentile4.683424568
Maximum4.843548207
Range0.8234989134
Interquartile range (IQR)0.1705068454

Descriptive statistics

Standard deviation0.1348539251
Coefficient of variation (CV)0.03006117139
Kurtosis-0.2042680098
Mean4.485983709
Median Absolute Deviation (MAD)0.08296221515
Skewness-0.5284483943
Sum1171913.898
Variance0.01818558111
MonotonicityNot monotonic
2022-02-27T16:49:39.494316image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.4983408744
 
< 0.1%
4.5719696874
 
< 0.1%
4.561284894
 
< 0.1%
4.4569808914
 
< 0.1%
4.5370466493
 
< 0.1%
4.4812186533
 
< 0.1%
4.4700712493
 
< 0.1%
4.6805769193
 
< 0.1%
4.6358908783
 
< 0.1%
4.4838157773
 
< 0.1%
Other values (252284)261205
> 99.9%
ValueCountFrequency (%)
4.0200492941
< 0.1%
4.0211768541
< 0.1%
4.0216859011
< 0.1%
4.0218122911
< 0.1%
4.0220891911
< 0.1%
4.0226070591
< 0.1%
4.0226611161
< 0.1%
4.0229835571
< 0.1%
4.0241089161
< 0.1%
4.0248854931
< 0.1%
ValueCountFrequency (%)
4.8435482071
< 0.1%
4.8329221581
< 0.1%
4.8243017271
< 0.1%
4.8225215281
< 0.1%
4.8223750891
< 0.1%
4.8198417151
< 0.1%
4.8189363821
< 0.1%
4.8181538361
< 0.1%
4.815300031
< 0.1%
4.8076067021
< 0.1%

g
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct249347
Distinct (%)95.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.382739815
Minimum3.918099098
Maximum4.737899203
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 MiB
2022-02-27T16:49:39.588066image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum3.918099098
5-th percentile4.119480038
Q14.304437372
median4.427937579
Q34.479511744
95-th percentile4.543871127
Maximum4.737899203
Range0.8198001045
Interquartile range (IQR)0.1750743723

Descriptive statistics

Standard deviation0.1365972716
Coefficient of variation (CV)0.03116709579
Kurtosis-0.07968804888
Mean4.382739815
Median Absolute Deviation (MAD)0.0674608924
Skewness-0.8739160506
Sum1144942.566
Variance0.01865881462
MonotonicityNot monotonic
2022-02-27T16:49:39.666191image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.4829994484
 
< 0.1%
4.4391047384
 
< 0.1%
4.4902338054
 
< 0.1%
4.4932394054
 
< 0.1%
4.4630666934
 
< 0.1%
4.2076384844
 
< 0.1%
4.4552500774
 
< 0.1%
4.4177424273
 
< 0.1%
4.503551833
 
< 0.1%
4.4864632633
 
< 0.1%
Other values (249337)261202
> 99.9%
ValueCountFrequency (%)
3.9180990981
< 0.1%
3.9185152321
< 0.1%
3.9185232461
< 0.1%
3.9187794871
< 0.1%
3.9187859741
< 0.1%
3.9193400821
< 0.1%
3.9198484171
< 0.1%
3.9203924941
< 0.1%
3.9215641031
< 0.1%
3.9216327461
< 0.1%
ValueCountFrequency (%)
4.7378992031
< 0.1%
4.7335455121
< 0.1%
4.729659841
< 0.1%
4.7277271751
< 0.1%
4.7231562761
< 0.1%
4.7220419521
< 0.1%
4.7201963671
< 0.1%
4.7196512821
< 0.1%
4.7192448931
< 0.1%
4.7184627351
< 0.1%

r
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct249353
Distinct (%)95.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.295851195
Minimum3.852798192
Maximum4.559329363
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 MiB
2022-02-27T16:49:39.759941image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum3.852798192
5-th percentile4.053695822
Q14.209568933
median4.335761495
Q34.390298195
95-th percentile4.460934995
Maximum4.559329363
Range0.7065311708
Interquartile range (IQR)0.1807292627

Descriptive statistics

Standard deviation0.1301458051
Coefficient of variation (CV)0.03029569676
Kurtosis-0.2458807453
Mean4.295851195
Median Absolute Deviation (MAD)0.07508624542
Skewness-0.7660494023
Sum1122243.87
Variance0.0169379306
MonotonicityNot monotonic
2022-02-27T16:49:39.850106image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.3333047215
 
< 0.1%
4.3527210315
 
< 0.1%
4.3503517685
 
< 0.1%
4.383863935
 
< 0.1%
4.3506485814
 
< 0.1%
4.3245741664
 
< 0.1%
4.3454618094
 
< 0.1%
4.3581999464
 
< 0.1%
4.3492833884
 
< 0.1%
4.3373767794
 
< 0.1%
Other values (249343)261195
> 99.9%
ValueCountFrequency (%)
3.8527981921
< 0.1%
3.8530006831
< 0.1%
3.8535155671
< 0.1%
3.8535738521
< 0.1%
3.8535829331
< 0.1%
3.8536762431
< 0.1%
3.8540018331
< 0.1%
3.8540155021
< 0.1%
3.8541640521
< 0.1%
3.8542703921
< 0.1%
ValueCountFrequency (%)
4.5593293631
< 0.1%
4.5584232851
< 0.1%
4.556603841
< 0.1%
4.5530775281
< 0.1%
4.552044951
< 0.1%
4.5520007311
< 0.1%
4.549738841
< 0.1%
4.5491834881
< 0.1%
4.5490405811
< 0.1%
4.5490028021
< 0.1%

i
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct249641
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.252026764
Minimum3.805581894
Maximum4.604602567
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 MiB
2022-02-27T16:49:39.959494image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum3.805581894
5-th percentile4.01924759
Q14.167901285
median4.278399797
Q34.338730964
95-th percentile4.439376422
Maximum4.604602567
Range0.7990206728
Interquartile range (IQR)0.1708296789

Descriptive statistics

Standard deviation0.1293494342
Coefficient of variation (CV)0.03042065381
Kurtosis-0.2125414486
Mean4.252026764
Median Absolute Deviation (MAD)0.07887863257
Skewness-0.5430907124
Sum1110795.22
Variance0.01673127613
MonotonicityNot monotonic
2022-02-27T16:49:40.053244image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.2984554594
 
< 0.1%
4.3191884864
 
< 0.1%
4.2866188224
 
< 0.1%
4.083381294
 
< 0.1%
4.3068355874
 
< 0.1%
4.3003029884
 
< 0.1%
4.2753481574
 
< 0.1%
4.2909398864
 
< 0.1%
4.2833350954
 
< 0.1%
4.2677834174
 
< 0.1%
Other values (249631)261199
> 99.9%
ValueCountFrequency (%)
3.8055818941
< 0.1%
3.8080761921
< 0.1%
3.8097279551
< 0.1%
3.8105458271
< 0.1%
3.8107853821
< 0.1%
3.8109320771
< 0.1%
3.8113498761
< 0.1%
3.8114105061
< 0.1%
3.8122398521
< 0.1%
3.8127317071
< 0.1%
ValueCountFrequency (%)
4.6046025671
< 0.1%
4.6043321951
< 0.1%
4.6036526321
< 0.1%
4.6028625011
< 0.1%
4.6016975861
< 0.1%
4.6011135571
< 0.1%
4.5996489091
< 0.1%
4.598444891
< 0.1%
4.5931800281
< 0.1%
4.5916064791
< 0.1%

z
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct249621
Distinct (%)95.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.226446294
Minimum3.761532191
Maximum4.590421537
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.0 MiB
2022-02-27T16:49:40.146994image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum3.761532191
5-th percentile3.9924826
Q14.140877122
median4.247230599
Q34.311789468
95-th percentile4.426415129
Maximum4.590421537
Range0.8288893451
Interquartile range (IQR)0.170912346

Descriptive statistics

Standard deviation0.1321760473
Coefficient of variation (CV)0.03127356605
Kurtosis-0.1470461671
Mean4.226446294
Median Absolute Deviation (MAD)0.0800843381
Skewness-0.4077818677
Sum1104112.603
Variance0.01747050749
MonotonicityNot monotonic
2022-02-27T16:49:40.240744image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4.2486859444
 
< 0.1%
4.2596153784
 
< 0.1%
4.2320859434
 
< 0.1%
4.2439475564
 
< 0.1%
4.2867847684
 
< 0.1%
4.2690217724
 
< 0.1%
4.2371792854
 
< 0.1%
4.2641215784
 
< 0.1%
4.2627424564
 
< 0.1%
4.2741705494
 
< 0.1%
Other values (249611)261199
> 99.9%
ValueCountFrequency (%)
3.7615321911
< 0.1%
3.7728250311
< 0.1%
3.7742980151
< 0.1%
3.7758896741
< 0.1%
3.7768147351
< 0.1%
3.7770027071
< 0.1%
3.7778948721
< 0.1%
3.7795318421
< 0.1%
3.7799507461
< 0.1%
3.7800361291
< 0.1%
ValueCountFrequency (%)
4.5904215371
< 0.1%
4.5903531461
< 0.1%
4.5899798751
< 0.1%
4.5898810911
< 0.1%
4.5896459941
< 0.1%
4.5895259141
< 0.1%
4.5894054051
< 0.1%
4.5893632151
< 0.1%
4.5879895231
< 0.1%
4.5879260571
< 0.1%

uErr
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct229565
Distinct (%)87.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-1.635966937
Minimum-6.390592991
Maximum2.643517059
Zeros0
Zeros (%)0.0%
Negative232411
Negative (%)89.0%
Memory size2.0 MiB
2022-02-27T16:49:40.352829image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-6.390592991
5-th percentile-4.59506201
Q1-2.631510999
median-1.251178138
Q3-0.4435980531
95-th percentile0.2963907995
Maximum2.643517059
Range9.034110049
Interquartile range (IQR)2.187912946

Descriptive statistics

Standard deviation1.542026569
Coefficient of variation (CV)-0.9425780767
Kurtosis-0.5023515132
Mean-1.635966937
Median Absolute Deviation (MAD)0.9505485342
Skewness-0.6764664902
Sum-427378.3667
Variance2.37784594
MonotonicityNot monotonic
2022-02-27T16:49:40.430967image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-3.8746133956
 
< 0.1%
-3.9815139486
 
< 0.1%
-4.6649650126
 
< 0.1%
-3.3430149586
 
< 0.1%
-3.4106583596
 
< 0.1%
-4.8651009235
 
< 0.1%
-4.4602426415
 
< 0.1%
-4.4443565865
 
< 0.1%
-4.0487106225
 
< 0.1%
-4.8138848895
 
< 0.1%
Other values (229555)261184
> 99.9%
ValueCountFrequency (%)
-6.3905929911
< 0.1%
-6.3500148911
< 0.1%
-6.309974531
< 0.1%
-6.2379727171
< 0.1%
-6.2080142741
< 0.1%
-6.1943212261
< 0.1%
-6.1870500411
< 0.1%
-6.1812803021
< 0.1%
-6.1763680161
< 0.1%
-6.1711604771
< 0.1%
ValueCountFrequency (%)
2.6435170591
< 0.1%
2.5350155281
< 0.1%
2.5298896451
< 0.1%
2.5194566081
< 0.1%
2.4929314441
< 0.1%
2.4757969731
< 0.1%
2.4664840831
< 0.1%
2.4093021311
< 0.1%
2.4005671661
< 0.1%
2.3468712471
< 0.1%

gErr
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct168660
Distinct (%)64.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3.16939416
Minimum-5.50720542
Maximum2.199562421
Zeros0
Zeros (%)0.0%
Negative260509
Negative (%)99.7%
Memory size2.0 MiB
2022-02-27T16:49:40.587217image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-5.50720542
5-th percentile-5.030607446
Q1-4.264970069
median-3.020715071
Q3-2.288846976
95-th percentile-1.265936679
Maximum2.199562421
Range7.706767841
Interquartile range (IQR)1.976123094

Descriptive statistics

Standard deviation1.211484381
Coefficient of variation (CV)-0.3822447822
Kurtosis-0.7749272392
Mean-3.16939416
Median Absolute Deviation (MAD)0.9133470116
Skewness0.05384343992
Sum-827969.3611
Variance1.467694404
MonotonicityNot monotonic
2022-02-27T16:49:40.680967image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4.91667632713
 
< 0.1%
-4.94697209912
 
< 0.1%
-4.84991870211
 
< 0.1%
-4.9145427111
 
< 0.1%
-4.82059596211
 
< 0.1%
-4.86969113811
 
< 0.1%
-4.90055666211
 
< 0.1%
-4.71134141211
 
< 0.1%
-4.92077824311
 
< 0.1%
-4.72405848411
 
< 0.1%
Other values (168650)261126
> 99.9%
ValueCountFrequency (%)
-5.507205421
< 0.1%
-5.4980483271
< 0.1%
-5.4778478061
< 0.1%
-5.4747008311
< 0.1%
-5.4706008071
< 0.1%
-5.4679164841
< 0.1%
-5.4675972551
< 0.1%
-5.4640903811
< 0.1%
-5.4614817011
< 0.1%
-5.4613545691
< 0.1%
ValueCountFrequency (%)
2.1995624211
< 0.1%
1.869196281
< 0.1%
1.8216265491
< 0.1%
1.669006351
< 0.1%
1.6356304281
< 0.1%
1.6004548371
< 0.1%
1.5357459221
< 0.1%
1.438216191
< 0.1%
1.424735091
< 0.1%
1.4004641541
< 0.1%

rErr
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct140154
Distinct (%)53.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3.324471572
Minimum-4.871717159
Maximum-0.8726651942
Zeros0
Zeros (%)0.0%
Negative261239
Negative (%)100.0%
Memory size2.0 MiB
2022-02-27T16:49:40.790342image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-4.871717159
5-th percentile-4.4486661
Q1-4.009111923
median-3.335684649
Q3-2.751533171
95-th percentile-1.975968038
Maximum-0.8726651942
Range3.999051964
Interquartile range (IQR)1.257578751

Descriptive statistics

Standard deviation0.7784262254
Coefficient of variation (CV)-0.234150363
Kurtosis-0.8236872328
Mean-3.324471572
Median Absolute Deviation (MAD)0.6313183475
Skewness0.2565939663
Sum-868481.629
Variance0.6059473884
MonotonicityNot monotonic
2022-02-27T16:49:40.872390image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-4.29211480113
 
< 0.1%
-4.50092001312
 
< 0.1%
-4.1772029712
 
< 0.1%
-4.24359152412
 
< 0.1%
-4.30431969511
 
< 0.1%
-4.31539308311
 
< 0.1%
-4.22353548911
 
< 0.1%
-4.43016674611
 
< 0.1%
-4.1524648311
 
< 0.1%
-4.13623912311
 
< 0.1%
Other values (140144)261124
> 99.9%
ValueCountFrequency (%)
-4.8717171591
< 0.1%
-4.8582637911
< 0.1%
-4.8512506761
< 0.1%
-4.8490452611
< 0.1%
-4.8405878161
< 0.1%
-4.8357183031
< 0.1%
-4.8316044251
< 0.1%
-4.827993891
< 0.1%
-4.825619151
< 0.1%
-4.8246376411
< 0.1%
ValueCountFrequency (%)
-0.87266519421
< 0.1%
-0.87766654491
< 0.1%
-0.87874848071
< 0.1%
-0.88275179661
< 0.1%
-0.88652618981
< 0.1%
-0.88769220021
< 0.1%
-0.89345334871
< 0.1%
-0.90519912591
< 0.1%
-0.91226018791
< 0.1%
-0.91525537911
< 0.1%

iErr
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct132785
Distinct (%)50.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-3.206974193
Minimum-4.659959645
Maximum-0.3550325552
Zeros0
Zeros (%)0.0%
Negative261239
Negative (%)100.0%
Memory size2.0 MiB
2022-02-27T16:49:40.981752image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-4.659959645
5-th percentile-4.120244054
Q1-3.742690008
median-3.333385185
Q3-2.834472617
95-th percentile-1.786928249
Maximum-0.3550325552
Range4.30492709
Interquartile range (IQR)0.9082173917

Descriptive statistics

Standard deviation0.7127209008
Coefficient of variation (CV)-0.2222409218
Kurtosis0.6370570431
Mean-3.206974193
Median Absolute Deviation (MAD)0.445066823
Skewness0.9238053272
Sum-837786.7313
Variance0.5079710824
MonotonicityNot monotonic
2022-02-27T16:49:41.075515image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-3.70321958312
 
< 0.1%
-3.8672468211
 
< 0.1%
-3.68774376411
 
< 0.1%
-3.71024578511
 
< 0.1%
-3.80272841211
 
< 0.1%
-3.83363932811
 
< 0.1%
-3.72506926211
 
< 0.1%
-4.04173191911
 
< 0.1%
-3.73333457611
 
< 0.1%
-3.53118941510
 
< 0.1%
Other values (132775)261129
> 99.9%
ValueCountFrequency (%)
-4.6599596451
< 0.1%
-4.6245101011
< 0.1%
-4.5931107261
< 0.1%
-4.5927277481
< 0.1%
-4.5906058051
< 0.1%
-4.5826329871
< 0.1%
-4.5820108831
< 0.1%
-4.5726770311
< 0.1%
-4.5706529181
< 0.1%
-4.5685974061
< 0.1%
ValueCountFrequency (%)
-0.35503255521
< 0.1%
-0.3551322011
< 0.1%
-0.3554274881
< 0.1%
-0.35693069751
< 0.1%
-0.35739083751
< 0.1%
-0.35751652381
< 0.1%
-0.35776977781
< 0.1%
-0.35952899421
< 0.1%
-0.36091419781
< 0.1%
-0.36304645351
< 0.1%

zErr
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct167166
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-2.586706661
Minimum-4.50409203
Maximum0.1406805099
Zeros0
Zeros (%)0.0%
Negative260170
Negative (%)99.6%
Memory size2.0 MiB
2022-02-27T16:49:41.153640image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Quantile statistics

Minimum-4.50409203
5-th percentile-3.663245885
Q1-3.201662427
median-2.769974106
Q3-2.174807037
95-th percentile-0.7640455578
Maximum0.1406805099
Range4.64477254
Interquartile range (IQR)1.02685539

Descriptive statistics

Standard deviation0.8563588551
Coefficient of variation (CV)-0.3310614489
Kurtosis0.5116249619
Mean-2.586706661
Median Absolute Deviation (MAD)0.4899981137
Skewness0.9632662253
Sum-675748.6614
Variance0.7333504888
MonotonicityNot monotonic
2022-02-27T16:49:41.247390image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-3.1175870189
 
< 0.1%
-3.2022000869
 
< 0.1%
-3.099568658
 
< 0.1%
-3.2567004728
 
< 0.1%
-3.3431027978
 
< 0.1%
-2.9580505658
 
< 0.1%
-3.2683440498
 
< 0.1%
-3.131705178
 
< 0.1%
-3.3511480498
 
< 0.1%
-3.278555598
 
< 0.1%
Other values (167156)261157
> 99.9%
ValueCountFrequency (%)
-4.504092031
< 0.1%
-4.4966471941
< 0.1%
-4.4846468291
< 0.1%
-4.4732580881
< 0.1%
-4.4604967211
< 0.1%
-4.4198776761
< 0.1%
-4.408558021
< 0.1%
-4.3953213541
< 0.1%
-4.3923188651
< 0.1%
-4.3921068051
< 0.1%
ValueCountFrequency (%)
0.14068050991
< 0.1%
0.14063470621
< 0.1%
0.14060984081
< 0.1%
0.14024073451
< 0.1%
0.14021978951
< 0.1%
0.14003781671
< 0.1%
0.13995795091
< 0.1%
0.13967249281
< 0.1%
0.13960308391
< 0.1%
0.13953498131
< 0.1%

Interactions

2022-02-27T16:49:37.142974image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:22.473887image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:24.108924image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:25.668407image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:27.325846image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:28.948868image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:30.584221image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:32.208869image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:33.814939image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:35.520945image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:37.294229image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:22.625495image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:24.264030image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:25.820854image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:27.493026image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:29.177582image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:30.736558image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:32.378360image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:33.981784image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:35.671152image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:37.444824image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:22.776107image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:24.420399image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:25.970470image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:27.644847image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:29.316638image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:30.888872image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:32.527109image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:34.148667image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:35.821398image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:37.611387image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:22.945666image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:24.567478image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:26.138780image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:27.809104image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:29.484175image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:31.054010image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:32.693855image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:34.379074image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:35.987786image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:37.764159image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:23.109418image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:24.733664image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:26.314714image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:27.977665image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:29.648832image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:31.206673image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:32.860210image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:34.535265image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:36.140977image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:37.927958image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:23.260396image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:24.884769image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:26.471389image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:28.145319image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:29.799332image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:31.373686image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:33.013298image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:34.703008image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:36.305362image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:38.078986image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:23.412710image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:25.035141image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:26.686693image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:28.297086image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:29.949851image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:31.524017image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:33.177806image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:34.866998image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:36.457488image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:38.230159image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:23.577973image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:25.200146image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:26.841714image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:28.463840image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:30.117282image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:31.737709image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:33.345595image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:35.038734image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:36.619009image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:38.398447image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:23.744855image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:25.367450image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:27.007739image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:28.631466image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:30.268834image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:31.909431image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:33.512875image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:35.201596image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:36.781370image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:38.549019image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:23.897801image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:25.518462image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:27.174815image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:28.798431image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:30.435187image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:32.057472image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:33.663643image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:35.353913image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
2022-02-27T16:49:36.988943image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Correlations

2022-02-27T16:49:41.341131image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2022-02-27T16:49:41.438012image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2022-02-27T16:49:41.547387image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2022-02-27T16:49:41.719267image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/

Phik (φk)

Phik (φk) is a new and practical correlation coefficient that works consistently between categorical, ordinal and interval variables, captures non-linear dependency and reverts to the Pearson correlation coefficient in case of a bivariate normal input distribution. There is extensive documentation available here.

Missing values

2022-02-27T16:49:38.672898image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
A simple visualization of nullity by column.
2022-02-27T16:49:38.881101image/svg+xmlMatplotlib v3.5.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

First rows

ugrizuErrgErrrErriErrzErr
04.6527954.4746294.4099234.3139614.2799990.049153-2.190780-2.272632-2.762710-2.128560
14.4535614.2827694.1995144.1663544.141022-1.171849-4.042968-3.947662-3.836893-3.368879
24.3908514.3417604.2833524.2654904.247485-2.735812-3.819903-3.701041-3.546751-2.916382
34.3497884.2715484.1612124.1222644.102762-1.592327-3.141844-3.436010-3.423867-2.972008
44.5793714.5514344.3403144.2603164.2139030.6116070.047420-2.494207-2.911924-2.741927
54.3577644.2690744.2349984.2140694.208035-3.056323-4.482291-4.022824-3.796060-3.339769
64.4414864.3202944.2404574.1999944.172903-1.662483-4.012729-3.974966-3.864849-3.557718
74.3287864.2333384.1852524.1605954.142042-2.843298-4.194295-3.774952-3.547864-3.101994
84.3207484.2331084.1633414.1289874.107575-3.429389-4.565281-4.208628-3.999146-3.696078
94.6207094.4254654.2869484.2419494.216785-0.206369-2.476811-3.458386-3.450321-3.103916

Last rows

ugrizuErrgErrrErriErrzErr
2612294.6958474.4886924.4208244.3922444.418876-0.813043-2.404596-2.616923-2.483001-1.057818
2612304.5631184.4724234.3945044.3662184.3377310.219479-2.267288-2.564982-2.397699-1.826473
2612314.6449874.5587994.4186604.3726914.3320180.222662-0.968732-2.465651-2.551260-2.189674
2612324.5926394.4992544.4652494.4705514.509733-0.251317-2.622918-2.372543-1.757940-0.698375
2612334.6321264.5904884.4678174.4324074.403935-0.273460-1.091046-2.308266-2.330313-1.758458
2612344.6424964.6205984.4615054.4112844.442437-0.008877-0.423222-2.075477-2.296403-0.845961
2612354.4669624.5197594.4523684.4358634.403369-1.746984-1.795949-2.069167-1.799717-1.255612
2612364.6469244.5502404.4574714.4460154.443894-0.058686-1.415557-2.162706-1.789232-0.830606
2612374.5557524.5766584.4903504.5437074.490156-0.588459-1.229162-1.883566-0.567774-0.669251
2612384.5759514.5645164.4999094.4378344.373503-0.006240-1.072028-1.394051-1.839400-1.751961